Expires soon Amazon

Big Data Prototyping Architect

  • The City (London)
  • Chemistry / Biology / Agronomy

Job description



DESCRIPTION

Amazon Web Services (AWS) EMEA is looking for an experienced Data and Analytics specialist, who will take the role of a prototype developer, working with AWS customers to support designing complex data and analytics solutions leveraging AWS services.

The Data Prototype Architect will be part of EMEA Prototyping Labs and will work in close partnership with the Sales and Business Development teams to enable large-scale customer use cases and drive the adoption AWS Advanced Analytics services.

The Data Prototype Architect will engage directly with the customers' development team, understand their specific business and technology challenges in the area of data and advance analytics, support hands-on to build data lakes, database, DW and analytics prototypes and transfer knowledge on specific AWS services, e.g. Elastic Map Reduce (EMR), Redshift, Kinesis, Amazon Athena, Data Pipeline, S3, DynamoDB, ElastiCache RDS, Redshift.

Prototyping engagements will usually require to travel to Customers across EMEA and work 2-3 weeks on-site in a temporary Lab-like environment.

The Data Prototype Developer will also provide field enablement support for the wider Prototyping Labs Competencies, e.g. IoT, Virtual Reality/ Augmented Reality, Voice and Image Recognition to integrate Data & Analytics services into wider more complex customer prototypes.

Ideal candidate profile



BASIC QUALIFICATIONS

· BS in Computer Science or related field
· 4+ years of software development experience
· Extensive knowledge of working with large data sets and converging data pipelines
· Proficiency in object oriented development
· Demonstrated experience and passion for analytics, working in distributed environments, and economic principles
· Deep understanding and implementation of database, analytics, and management concepts / technologies in the industry, to include RDBMS systems, NoSQL systems, ETL / ELT tools, BI Reporting, Dashboards, MPP / SMP databases, Big Data, Hadoop, Data Science, Data Security, Data Integration, Data Warehousing and EMR (Hive, Pig, Spark), Data Governance, Data Lakes. There is not an expectation to be proficient in all of these, but hands-on implementation experience in at least some of these topics is required.
· Good experience with Kubernetes, EKS, Istio, Containerization, Docker, Microservices
· Proficiency with programming languages such as Python, Scala and R, Java, data querying tools, and performance analyzers.